PubMed · 12957536
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Thomas Werner. 2003. Yeast expression-array analysis goes molecular.. https://doi.org/10.1016/s0168-9525(03)00197-5
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STALARD (selective target amplification for low-abundance RNA detection) enables isoform-level quantification of low-abundance RNAs using conventional laboratory equipment. Here, we describe steps for RNA isolation, primer design, reverse transcription, selective target amplification, and downstream analysis. The protocol couples selective pre-amplification with a quantitative reverse-transcription PCR (RT-qPCR) readout and optional nanopore sequencing. Using 1 μg input RNA and 12 pre-amplification cycles, STALARD reduces Cq values by approximately 10-12 cycles, bringing the target into a reliably quantifiable range. For complete details on the use and execution of this protocol, please refer to Jeong et al.1.
We present a critical assessment of the promise and pitfalls of genotype versus gene function measures in cancer epidemiology studies. While both measures have pros and cons and are complementary, in terms of potential for contributing knowledge that directly leads to prevention, we argue that attention should be given to research relating functional parameters (single protein expression, functional or phenotypic assays or patterns of gene/protein expression) to disease risk. We present the theoretical and conceptual basis of why studies focusing on polymorphisms in the low-penetrance genes may be logically less fruitful for making inroads to cancer prevention than appropriately designed studies using validated functional parameters. We then substantiate these arguments with some concrete examples based on the current literature. We also discuss the limitations of including functional parameters in epidemiological studies and technical improvements required before such studies can truly fulfil their promise. Finally, we offer some specific recommendations for future research directions in this area.
Short interfering RNA (siRNA) is widely used for studying gene function and holds great promise as a tool for validating drug targets and treating disease. A critical assumption in these applications is that the effect of siRNA on cells is specific, i.e., limited to the specific knockdown of the target gene. In this article, we characterize the specificity of siRNA by applying gene expression profiling. Several siRNAs were designed against different regions of the same target gene for three different targets. Their effects on cells were compared by using DNA microarrays to generate gene expression signatures. When the siRNA design and transfection conditions were optimized, the signatures for different siRNAs against the same target were shown to correlate very closely, whereas the signatures for different genes revealed no correlation. These results indicate that siRNA is a highly specific tool for targeted gene knockdown, establishing siRNA-mediated gene silencing as a reliable approach for large-scale screening of gene function and drug target validation.